From Automation to Agentic Ops: What GCCs Will Be Delegating to AI in 2026

In 2026, Global Capability Centres (GCCs) aren’t just automating routine work. They’re moving into agentic operations — AI systems that can interpret goals, make decisions, execute tasks autonomously within guardrails, and adapt in real time. This shift marks a fundamental change in how GCCs deliver strategic value, how global teams are structured, and how organizations think about GCC services and global talent acquisition. While India often leads in scale and maturity, the trends we explore here are global and relevant to any leader planning growth, innovation, or transformation through GCCs.

Summary

Purpose:
To unpack how GCCs are progressing beyond automation into agentic AI operations, the functions being delegated in 2026, and the strategic implications for talent, governance, and value delivery.

Structure:

1. Why GCCs Are Evolving to Agentic Ops
   
2. Defining Agentic Operations for GCCs
   
3. What Work GCCs Will Delegate to AI in 2026
   
4. Organizational and Talent Impacts
   
5. How Leaders Should Implement Agentic AI
   
6. Future Outlook for GCCs
   

Use Cases:

• Executives planning GCC services transformation
  
• Talent leaders redefining global talent acquisition strategies
  
• COOs driving digital and AI transformation
  
• Capability centre leaders balancing innovation and governance
  

Key Takeaways:

• GCCs are progressing from task automation to autonomous outcome delivery.
  
• Agentic AI augments strategic, analytical, and decision‑oriented work.
  
• Effective implementation hinges on governance, data, and talent evolution.
  

Why GCCs Are Evolving to Agentic Ops

Over the past decade, GCCs have been central to cost optimization and process standardization. Early waves of automation (RPA, scripting) eliminated repetitive tasks. But these technologies still required structured inputs and human supervision. As businesses mature, stakeholders expect GCCs to deliver strategic insight, cross‑functional problem solving, and decision support — not just labor arbitrage.

In parallel, AI technologies have matured. Modern AI systems can reason over unstructured data, manage multi‑step processes, and react to changes without explicit instructions. This capability shift is driving GCCs worldwide to reimagine their role: from back‑office execution hubs to autonomous value creators.

Agentic AI enables this by:

• Handling ambiguity and incomplete information
  
• Optimizing decisions to meet outcomes
  
• Learning continuously from feedback loops
  

This evolution resonates with the broader movement in GCC services toward delivering strategic, high‑impact work rather than manual throughput.

Defining Agentic Operations for GCCs

Agentic operations refers to systems that combine automation with autonomy. Instead of pre‑defined scripts, agentic AI operates against objectives and uses its internal models to determine how best to achieve them — within established boundaries.

Key characteristics include:

• Outcome orientation: Systems are designed to meet business objectives (e.g., improve forecast accuracy by 20%, reduce compliance risk) rather than execute steps.
  
• Dynamic decisioning: AI adapts strategies in real time based on data signals.
  
• Human‑AI collaboration: People define goals and guardrails; AI proposes and executes pathways.
  
• Explainability: Decisions and actions are traceable and auditable.
  

For GCC leaders, agentic ops represents a leap from automation with human oversight to shared responsibility for outcomes — reshaping how GCCs deliver value across functions.

What Work GCCs Are Delegating to AI in 2026

Here’s how GCCs are allocating work to agentic systems this year, organized by functional domains:

1. Strategic Finance and Predictive Planning

Finance functions within GCCs are transitioning from static reporting to forward‑looking decisioning. Agentic AI now:

• Runs scenario planning and stress tests automatically
  
• Generates insights in natural language
  
• Recommends budget reallocations
  
• Alerts leaders to risks or anomalies before quarter end
  

Instead of human teams running models, they validate and interpret AI‑generated insights.

2. Compliance, Risk, and Regulatory Intelligence

Regulatory landscapes are shifting faster than ever. Agentic AI systems:

• Continuously monitor global regulations
  
• Map requirements to business processes
  
• Suggest risk mitigation actions
  
• Simulate regulatory impact on operations
  

This empowers GCC services to stay ahead of compliance risk — a big shift from periodic audits.

3. Customer Experience Orchestration

Agentic AI is augmenting customer‑facing operations by:

• Creating personalized engagement flows
  
• Routing and escalating issues autonomously
  
• Identifying churn signals and suggesting retention actions
  

For GCCs managing support, experience, and CRM operations, this means higher satisfaction with smaller human teams focused on exceptions and empathy.

4. Talent Strategy, Workforce Optimization, and Engagement

AI is influencing how GCCs hire and retain talent:

• Matching candidates to roles using skills, behavioral data, and growth potential
  
• Identifying internal mobility pathways for high performers
  
• Anticipating turnover risk and recommending interventions
  
• Suggesting workforce mixes (human vs AI) based on cost and impact
  

This directly impacts global talent acquisition strategies, redefining roles from sourcing profiles to managing hybrid workforces.

5. R&D, Product Intelligence, and Innovation Pipelines

Some GCCs extend into innovation domains traditionally owned by HQ. Agentic AI:

• Scans research landscapes
  
• Proposes product hypotheses
  
• Runs simulations and feasibility analyses
  
• Assists with prototype testing
  

These capabilities blur the line between execution center and innovation hub — significantly expanding the mandate of modern GCCs.

Organizational and Talent Impacts

Rethinking Roles and Skills

Delegating work to agentic systems doesn’t eliminate human work — it transforms it. GCCs now emphasize roles like:

• AI Orchestration Lead
  
• Decision Intelligence Strategist
  
• AI Governance and Ethics Specialist
  
• Business‑AI Integration Manager
  

Traditional transactional roles are shifting toward interpretation, strategy, and oversight. This influences global talent acquisition priorities: hiring for judgment, creativity, and system design rather than routine execution.

Investing in AI Fluency

A foundational requirement for GCCs is building AI literacy across the organization. This includes:

• AI awareness training for leaders
  
• Hands‑on AI tools for practitioners
  
• Collaboration frameworks for human‑AI work
  

Companies that invest here see faster adoption, higher trust in AI decisions, and better operational outcomes.

Governance, Ethics, and Risk Management

With autonomy comes responsibility. Leaders must establish frameworks that ensure agentic systems act ethically, legally, and in alignment with strategy.

Key governance pillars include:

• Clear objectives and guardrails: Define what AI must do and must not do.
  
• Explainability tools: Ensure decisions can be traced and justified.
  
• Continuous monitoring: Track performance, bias, and drift.
  
• Human‑in‑the‑loop checkpoints: For high‑risk decisions (e.g., regulatory actions, large financial commitments).
  

Without robust governance, agentic ops may deliver speed without trust — undermining long‑term value.

How Leaders Should Implement Agentic AI

Here’s a practical roadmap for GCC leaders ready to embrace agentic operations:

Phase 1: Define Strategic Outcomes

Before implementing tools, teams must answer:

• What outcomes matter most right now?
  
• What KPIs will measure success?
  
• Where should AI have autonomy — and where should humans retain control?
  

Clarity at this stage prevents misalignment later.

Phase 2: Build the Data and Systems Foundation

Agentic AI thrives on structured, accessible data. Steps include:

• Unifying data sources across functions
  
• Standardizing governance and quality practices
  
• Creating APIs and data pipelines for real‑time access
  

Without this foundation, AI decisions will be inconsistent or shallow.

Phase 3: Pilot with Oversight

Start with a focused use case such as compliance intelligence or predictive planning:

• Establish human review checkpoints
  
• Evaluate performance against defined KPIs
  
• Capture lessons before scaling
  

Pilots help tune governance and build internal confidence.

Phase 4: Scale, Integrate, and Evolve Roles

As pilot results solidify, expand agentic systems to adjacent areas. Simultaneously:

• Redesign roles to reflect new workflows
  
• Update talent strategies to recruit and retain hybrid teams
  
• Invest in continuous learning and AI fluency
  

This stage transforms AI from a tool into a strategic partner.

What Success Looks Like in 2026

Successful GCCs in 2026 will demonstrate:

• Faster decision cycles with fewer manual inputs
  
• Higher operational resilience through proactive risk management
  
• Better talent engagement by elevating work to high‑impact areas
  
• Quantifiable business outcomes like improved forecast accuracy, faster compliance adaptation, and deeper customer insights
  

These centres will not be seen as cost centres; they will be strategic engines driving global performance.

Conclusion: A New Era for GCCs

The transition from simple automation to agentic operations signals a broader change in how organizations think about GCC services. AI is no longer a back‑office helper — it’s a collaborative partner that can own outcomes within human‑defined boundaries. For leaders rethinking global talent acquisition, workforce design, and operational strategy, the imperative is clear: design GCCs around purposeful autonomy, strong governance, and talent re‑skilling.

Agentic AI doesn’t replace human contribution — it amplifies it. Conducted well, this evolution enhances strategic insight, accelerates performance, and positions your GCC for long‑term value creation.

Want to lead in this new era of AI‑augmented operations? Ralent partners with global organizations to architect AI‑ready operating models, evolve talent strategies, and scale GCCs that thrive in the decade ahead.

By Ralent — Thought leaders in Global Capability Centres and AI‑augmented organizational strategy.

Sources: Gartner, McKinsey, Deloitte, Forrester, World Economic Forum, NASSCOM.